Radiotherapy is used to treat cancers and other ailments in mammalian (e.g., human and animal) tissue. One such radiotherapy technique is a Gamma Knife, by which a patient is irradiated by a large number of low-intensity gamma rays that converge with high intensity and high precision at a target (e.g., a tumor). In another embodiment, radiotherapy is provided using a linear accelerator, whereby a tumor is irradiated by high-energy particles (e.g., electrons, protons, ions and the like). The placement and dose of the radiation beam must be accurately controlled to ensure the tumor receives the prescribed radiation, and the placement of the beam should be such as to minimize damage to the surrounding healthy tissue.
Before administrating radiation doses to treat a patient, a treatment plan needs to be created, in which the manner of applying radiation doses are specified. A treatment plan is usually created based on a medical image (or a series of images) of the patient, in which an internal anatomical region of the patient is shown. From the medical image, the target to be treated is ascertained, as well as its location, size, and/or shape, based on which the directions and intensities of multiple radiation beams are determined such that the beams converge at the target location to provide the necessary radiation dose for treating the patient. While a physician may determine whether a particular object in the medical image is a target by visually observing the medical image, this process is often tedious and time consuming. Computer-aided image classification techniques can reduce the time to extract some or all required information from the medical image.
For example, some methods rely on training data to train a statistical model, and the trained statistical model may then be used to identify a target. However, the effectiveness of such methods depends largely on the quality of the training data. In order to obtain acceptable results, the training data have to contain accurately identified targets in terms of their location and segmentation. Usually, such high quality training data are in short supply.
In another example, pure image processing methods have been used to enhance the visibility of the medical image to allow the physician to better observe the medical image. Such methods, however, lack the classification ability to determine whether a particular object in the medical image is a target or not.
The present disclosure is directed to overcoming or mitigating one or more of these problems set forth.